Research On Employment Forecast And Application Of Higher Vocational Students

Since the enrollment expansion of colleges and universities,the state,the Ministry of Education and provincial education departments have put forward higher and higher requirements for the employment of college graduates,and the employment of graduates is more and more important for the healthy development of colleges and universities.How to seize the opportunity to meet the challenge and realize the enrollment expansion without reducing the quality of training is an important task to be solved urgently.Employment prediction refers to the prediction of whether students can get employment,the effective guidance for students with difficulty in predicting employment in advance,improve the employment rate of students,and promote the virtuous circle development of student enrollment expansion in higher vocational colleges.The existing research on employment prediction has some problems,such as low prediction accuracy and poor generalization performance.This paper firstly collects and sorts out the employment data and performance data of graduates from a higher vocational school from2016 to 2020,and then preprocesses them for the study of student employment prediction.First,design RXGRegressor from the data set level to solve the data loss problem,design adasyn-smote-RF algorithm to solve the data set sample imbalance problem,improve the accuracy of employment prediction by improving the quality of the data set.Then,the integrated prediction algorithm W＿voting is designed from the algorithm level to improve the accuracy of employment prediction through algorithm optimization.Finally,combine improving data quality and optimizing prediction algorithm,integrate RXGRegressor,Adasyn-SMOTE,W＿voting algorithm,design and implement RXGRegressor-ADASYN-SMOTE＿W＿voting algorithm.The experimental results show that the accuracy of the fusion algorithm on the 2016-2020 student employment prediction data set reaches 95.73%,which can meet the needs of practical application.The research of this paper is helpful for colleges and universities to find the students with employment difficulties as soon as possible,assist these students to establish the awareness of employment crisis in advance,and make positive and targeted preparations for employment,so as to improve the employment rate of higher vocational students.In addition,this paper uses big data technology to explore the factors that affect students’ employment,provide a basis for vocational colleges to design employment guidance programs,and provide technical support for the improvement of vocational graduates’ employment rate.